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monitoring-app

★ 34 Open GitHub ↗

Gravity application that provides a Kapacitor/Alertmanager/Grafana based monitoring system

// repository documentation

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# Gravity Cluster Monitoring

[Gravity](https://github.com/gravitational/gravity)'s Monitoring Application provides a
[Prometheus](https://prometheus.io/) and [Grafana](https://grafana.com/grafana/) based monitoring system.

## Grafana integration

This app is shipped with two pre-configured Grafana dashboards providing machine- and pod-level overview of the installed site.
The Grafana UI is integrated with Gravity control panel. To view dashboards, navigate to that site's `Monitoring` page.

Grafana is configured with anonymous mode which allows anyone logged into the Gravity WebUI to use it.

In development (sites installed with virsh locally) the anonymous mode has full Admin permissions that allows creating new and modifying existing dashboards which is convenient for development.

In production the anonymous mode is read-only that allows only viewing of existing dashboards.

## Pluggable dashboards

Other applications can ship their own Grafana dashboards by using ConfigMaps. A custom dashboard ConfigMap should be assigned a `monitoring`
label with value `dashboard` and created in the `monitoring` namespace for it to be recognized and loaded at startup:
```
apiVersion: v1
kind: ConfigMap
metadata:
  name: mydashboard
  namespace: monitoring
  labels:
    monitoring: dashboard
data:
  mydashboard: |
    { ... dashboard JSON ... }
```

An example of a dashboard ConfigMap can be seen in the monitoring-app's own resources.

A dashboard ConfigMap may contain multiple keys with dashboards, key names are not relevant. Dashboard JSON can be obtained from Grafana by building a dashboard and then exporting it (or viewing its raw JSON representation).

## Retention policies

The app comes with 3 pre-configured retention policies:

* default / 24h
* medium / 4w
* long / 52w

The `default` retention policy is supposed to store high-precision metrics (for example, all default metrics collected by heapster with 10s interval). The `default` policy is "default" for k8s database which means that metrics that do not specify retention policy explicitly go in there.

The other two policies - `medium` and `long` are supposed to store metric rollups and should not be used directly.

Durations for each of the retention policies can be configured via Gravity control panel.

## Rollups

Metric rollups are meant to provide access to historical data for longer time period but at lower resolution.

Monitoring app allows to configure two "types" of rollups for any collected metric.

* "medium" rollup aggregates (or filters) data over 5-minute interval and goes into "medium" retention policy
* "long" rollup aggregates (or filters) data over 1-hour interval and goes into "long" retention policy

This app comes with rollups pre-configured for some of the metrics collected by default. Applications that collect their own metrics can configure their own rollups as well, via ConfigMaps.

A custom rollup ConfigMap should be assigned a `monitoring` label with value `rollup` and created in the `monitoring` namespace
so it is recognized and loaded at startup:

```
apiVersion: v1
kind: ConfigMap
metadata:
  name: rollups-myrollups
  namespace: monitoring
  labels:
    monitoring: rollup
data:
  rollups: |
    [
      {
        "retention": "medium",
        "measurement": "cpu/usage_rate",
        "name": "cpu/usage_rate/medium",
        "functions": [
          {
            "function": "max",
            "field": "value",
            "alias": "value_max"
          },
          {
            "function": "mean",
            "field": "value",
            "alias": "value_mean"
          }
        ]
      }
    ]
```

Each rollup is a JSON object with the following fields:

* `retention` - name of the retention policy (and hence the aggregation interval) for this rollup, can be `medium` or `long`
* `measurement` - name of the metric for the rollup (i.e. which metric is being "rolled up")
* `name` - name of the resulting "rolled up" metric
* `functions` - list of rollup functions to apply to metric `measurement`
* `function` - function name, can be `mean`, `median`, `sum`, `max`, `min` or `percentile_XXX` where `0 <= XXX <= 100`
* `field` - name of the field to apply rollup function to (e.g. "value")
* `alias` - new name for the rolled up field (e.g. "value_max")

## Contributing

If you would like to improve Gravity's Monitoring Application, check out our
[contributing guidelines](./CONTRIBUTING.md) and [Code of Conduct](./CODE_OF_CONDUCT.md).

monitoring-app

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